The security enhancements delivered by SunRISE are demonstrated in the highly regulated environment of healthcare for which high levels of security are demanded for patient data.
The demonstration includes:
1. Unique identification of (capital intensive) medical devices
2. Authentication of third party equipment used in or with the medical device
3. Intrusion detection on the medical device and its local network (Monitoring Module) by parsing logs, detecting anomalies in user behaviour and unexpected changes to the device footprint.
4. Secure and trustable cooperative cloud-based monitoring of installed base (using secure and advanced cryptography like homomorphic or post-quantum cryptography)
The security benefits of SunRISE are demonstrated in the context of Energy Communities through the households of the Home Living Lab of Engie Laborelec. Electrical consumption and production are monitored and considered highly private.
Security and privacy preserving solutions such as SunRISE will help building a more trusted and resilient solution with the help of specific machine learning algorithms. In this use case, the SunRISE solution is used to:
1. Increase the security of the edge node through intrusion detection by analysing the ARM Performance Monitoring Unit of the device.
2. Detect abnormal electricity consumption of a single or co-located households
Cloud&Heat is operating various data centers that can be used as the basis for demonstrating the SunRISE technologies. They are equipped with sensors and actuators to monitor the status of the data center infrastructure, hardware and its cooling system.
In the scope of the SunRISE project, the partners leverage the existing infrastructure for an innovative IoT use case. In the underlying scenario, the data center sites are used for storing and processing data from the sensors, as well as evaluating the status of the infrastructure. In this use case, the SunRISE technology is applied to increase the security of the overall edge-cloud infrastructure, to improve its energy efficiency and to explore the potentials of predictive maintenance approaches.
Anomaly Detection in TSN Networks
Time-Sensitive Networking (TSN) describes standards that enable cross-vendor safety-critical real-time communication based on standard Ethernet. As part of the SunRISE project, a TSN demo is being developed at the Technical University of Munich to investigate the functionality and security of this new technology and its use in IoT. The latest hardware products implementing these standards are used. For example, it can be shown how a simulated master spoofing attack on clock synchronization (IEEE 1588 PTP) in the network, disrupts safety-critical motor control. In order to detect such attacks at an early stage, data is collected, annotated and trained.